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    • International Journal of Advanced Research in Engineering and Technology (IJARET), ISSN 0976 – 6480(Print), ISSN 0976 – 6499(Online) Volume 5, Issue 4, April (2014), pp. 46-56 © IAEME 46 APPLICATION OF BOX-WILSON EXPERIMENTAL DESIGN METHOD FOR ELECTROLESS COPPER PLATING Hameed Hussein Alwan Electrochemical Engineering Dept. / College of Engineering / Babylon University /Iraq ABSTRACT In this study, electroless copper plating was done by used Box-wilson experimental design as experimental design method to find the effect of most controllable variables on electroless copper plating process. To study these effect four variables were considered as most dominate variables. These variable are; Formalin concentration in rang 0.05-0.30 M, CuSO4 concentration in rang 0.005-0.045 M, temperature in rang 30-70 ° C and, pH solution in rang 11-13. These four variables are manipulated through experimental work by using Box-wilson experimental design by proposed second order polynomial model to correlate the studied effect of these variables on deposited copper layer thickness. The predicated models are found after analyzing statistically as follows: 222.0 369.0215.0306.0188.1207.1392.0663.0516.4 2 4 2 3 2 2 2 14321 X XXXXXXXy + +−−++++= Where y is the deposited copper layer thickness, X1 formalin concentration, X2 CuSO4 concentration , X3 temperature and , X4 solution pH . The study shows that formalin and CuSO4 concentrations have great significance effect on the deposited copper layer thickness while the temperature and pH solution have small dependence on layer thickness. Optimum conditions for getting the maximum deposited copper layer thickness are obtained by using optimization method on the above model. Keywords: Electroless Plating, Copper, Box-Wilson Experimental Design. INTERNATIONAL JOURNAL OF ADVANCED RESEARCH IN ENGINEERING AND TECHNOLOGY (IJARET) ISSN 0976 - 6480 (Print) ISSN 0976 - 6499 (Online) Volume 5, Issue 4, April (2014), pp. 46-56 © IAEME: www.iaeme.com/ijaret.asp Journal Impact Factor (2014): 7.8273 (Calculated by GISI) www.jifactor.com IJARET © I A E M E
    • International Journal of Advanced Research in Engineering and Technology (IJARET), ISSN 0976 – 6480(Print), ISSN 0976 – 6499(Online) Volume 5, Issue 4, April (2014), pp. 46-56 © IAEME 47 INTRODUCTION Electroless deposition of metals and alloys has a very significant practical importance in modern technology especially in the production of new materials for applications in electronics, wear and corrosion resistant materials, medical devices, battery technologies, etc. All solutions for electroless metal deposition have many similarities, but depending on the metal or alloy to be deposited, there are also some differences. Typically, the constituents of a solution for electroless metal deposition are; source of metal ions, complexing agent, reducing agents, stabilized and inhibitor i.e.electroless copper deposition, CuSo4 is used mainly as the source of copper ions. [1] Electroless plating is a wet chemical plating technique utilized by semiconductor industry to deposit thin films of metal or metal alloy over a substrate during fabrication or packaging of semiconductor devices. Electroless plating can be accomplished with relatively low cost tooling and materials as compared to electroplating. Further, Electroless plating is selective, provides excellent step coverage and good filling capabilities. [2] Electroless copper plating involves the reduction of copper ions to copper metal from solution contain copper ions i.e. CuSO4 and the surface catalyzed oxidation of a reducing agent. These processes are widely used in the fabrication of printed circuit boards due to their conformal deposition, low cost, and simple equipmental setup. Commercial electroless copper plating solutions often use formaldehyde or its derivatives as reducing agents because of their high deposition rate and the excellent mechanical properties of the copper deposits [1]. The complexing agent such as ethylene diaminetetra acetic acid EDTA, a reducing agent such as formalin and pH adjusting agent such as alkali hydroxide as main components. [3] The solution pH is a very important factor in the electroless deposition, indeed, it affects both anodic and cathodic reactions and various phenomena associated with the structure and composition of the metal-solution interphase. The plating rate increases remarkably when the solution pH increases[4]. MichinariSone et.al show that deposition rate increased with an increase in pH, fine copper particles were generated, and the stability of the bath decreased at a pH greater than 6.5. As the bath temperature increased, the deposition rate increased up to 50 ◦C, but particles were formed in the bath. [5] In this study, the Box-Wilson experimental design method was used in order to investigate the effects of important controllable variables on copper electroless plating. The experimental design is a response surface methodology used to evolution the dependent variable (thickness of copper deposited) as a function of independent variables (CuSO4 concentration, Formalin concentration, pH solution and Temperature). Optimum conditions for achieving the maximum film thickness deposited are obtain from optimizing the correlation. EXPERIMENTAL WORK Material Carbon steel (200 mm long x 50 mm wide x 2 mm thickness) as a substrate plate. Chemicals CuSO4 as a copper ions source, Formalin as reducing agent, EDTA as complexing agent and NaOH for pH adjusting. Procedure The substrate was mechanically polished down 1200 by emerypaper, dipped into 5% NaOH solution at 60 ӷ C for 5 minutes, rinsed with water and dipped in 15% HCl solution at room
    • International Journal of Advanced Research in Engineering and Technology (IJARET), ISSN 0976 – 6480(Print), ISSN 0976 – 6499(Online) Volume 5, Issue 4, April (2014), pp. 46-56 © IAEME 48 temperature for 2 minutes and, after that the substrate was dipped in the electroless plating solution (CuSO4, Formalin, EDTA and NaOH) the solution composition was prepare according to the experiment design. The substrate was weighted before and after immersion in a solution, the solution temperature was adjusted to desired value and for required time. The thickness of copper deposited thickness calculated by below equation: (1) 10)( 4 21 ρS WW Y ×− = Where Y= coating thickness in micron (µm). W1 = weight of a specimen before impressed in solution in gram W2 = weight of a specimen after impressed in solution in gram. S = surface area in dm2 . ρ = density in g / cm3 Box-wilson experiment design Box-wilson design is a response surface methodology RSM, and empirical modeling technique, devoted to the evaluation of relationship of a set of controlled experimental factors and observed results, the optimization process involves three step ;statistical design experiment , estimate coefficient for mathematical model , and predicting the response [6]. Response surface methodology or (RSM) is a collection of mathematical and statistical techniques useful for analyzing problems where several independent variables influence a dependent variable or response, and the goal is to optimize this response X1, X2 …. And Xq denote the independent variable that are continues and controllable by the experimenter with negligible error. [7-8] The operating parameters: concentration of reduction agent formalin (X1), copper ion concentration (X2), operating temperature (X3), and solution pH (X4). The response is the thickness of copper deposited layer (y).For four variables the quadratic polynomial equation can be represented as follows: (3) (2) 43144213321241113110219 2 48 2 37 2 26 2 1544332211 2 11 XXbXXbXXbXXbXXbXXb XbXbXbXbXbXbXbXbby XXbXbXbby jii q jii q iii q i +++++ ++++++++=∴ +∑+∑+= ∑ ∑== o o Where y is the predicated copper layer thickness (µm) b0 constant , b1, b2, b3 and, b4 linear coefficients, b5, b6, b7 and b8 quadratic coefficients, b9 , b10, b11, b12, b13 and, b14 cross-product coefficients. q, number of variables and in this case are q = 4.
    • International Journal of Advanced Research in Engineering and Technology (IJARET), ISSN 0976 – 6480(Print), ISSN 0976 – 6499(Online) Volume 5, Issue 4, April (2014), pp. 46-56 © IAEME 49 A preliminary step is to set up between coded level and the corresponding real variables which are required to determine the experimental range by the following equation: (4) min q XX XX X cen cenreal coded − − = The number of experimental run required to cover range for four variables in this case. (6)284422 (5)422 4 =+×+= ++= N qN q The coded variables tae values between -2 and 2, and according to these values the range of real variables for the system can be represented in tables(1) and (2). Table (1): The experimental range of variables Reduction agent concentration (M) Copper sulfate concentration (M) Temperature (° C) pH 0.05-0.3 0.005-0.045 30-70 11-13 Table (2): Relationship between coded and real variables Variables Levels X1,X2,X3, X4 -2 -1 0 1 2 X1=Reduction agent concentration (M) 0.05 0.1125 0.175 0.2375 0.3 X2=Copper sulfate concentration (M) 0.005 0.015 0.025 0.035 0.045 X3=Temperature(° C) 30 40 50 60 70 X4=pH 11 11.5 12 12.5 13
    • International Journal of Advanced Research in Engineering and Technology (IJARET), ISSN 0976 – 6480(Print), ISSN 0976 – 6499(Online) Volume 5, Issue 4, April (2014), pp. 46-56 © IAEME 50 Table (3): experimental design condition according to a Box-Wilson experiment design with four independent variables coded real x1 x2 x3 x4 Formalin Conc. M CuSO4 Conc. M Temp. ° C pH 1 -1 -1 -1 -1 0.1125 0.015 40 11.5 2 1 -1 -1 -1 0.2375 0.015 40 11.5 3 -1 1 -1 -1 0.1125 0.035 40 11.5 4 1 1 -1 -1 0.2375 0.035 40 11.5 5 -1 -1 1 -1 0.1125 0.015 60 11.5 6 1 -1 1 -1 0.2375 0.015 60 11.5 7 -1 1 1 -1 0.1125 0.035 60 11.5 8 1 1 1 -1 0.2375 0.035 60 11.5 9 -1 -1 -1 1 0.1125 0.015 40 12.5 10 1 -1 -1 1 0.2375 0.015 40 12.5 11 -1 1 -1 1 0.1125 0.035 40 12.5 12 1 1 -1 1 0.2375 0.035 40 12.5 13 -1 -1 1 1 0.1125 0.015 60 12.5 14 1 -1 1 1 0.2375 0.015 60 12.5 15 -1 1 1 1 0.1125 0.035 60 12.5 16 1 1 1 1 0.2375 0.035 60 12.5 17 -2 0 0 0 0.05 0.025 50 12 18 2 0 0 0 0.3 0.025 50 12 19 0 -2 0 0 0.175 0.005 50 12 20 0 2 0 0 0.175 0.045 50 12 21 0 0 -2 0 0.175 0.025 30 12 22 0 0 2 0 0.175 0.025 70 12 23 0 0 0 -2 0.175 0.025 50 11 24 0 0 0 2 0.175 0.025 50 13 25 0 0 0 0 0.175 0.025 50 12 26 0 0 0 0 0.175 0.025 50 12 27 0 0 0 0 0.175 0.025 50 12 28 0 0 0 0 0.175 0.025 50 12 RESULTS AND DISCUSSION Table 4- shows the experimental data (observed practically) and predicated (Calculated by software) values of the thickness of copper layer plated, the experimental results were modeled using a STATISTIC software Ver.5.5A, regression analysis to determine the coefficients of response model (equation 3). The calculated coefficients listed in table 5. The determination coefficient between the observed and predicated values was estimated of second order polynomial regression by using, the number of iterations was terminated when the proportion of variance accounted for was (99.87%) and the correlation factor R was equal (0.99937).
    • International Journal of Advanced Research in Engineering and Technology (IJARET), ISSN 0976 – 6480(Print), ISSN 0976 – 6499(Online) Volume 5, Issue 4, April (2014), pp. 46-56 © IAEME 51 Table (4): Experimental data and predicated values of the thickness of copper layer plated coded real Observed Experimenta l Thickness Y. Predicted thickness y Residual Ei=Y-yx1 x2 x3 x4 Formalin concentratio n (M) Copper sulfate concentratio n (M) Temp. ͦ C pH 1 -1 -1 -1 -1 0.1125 0.015 40 11.5 1.14 1.225 -0.085 2 1 -1 -1 -1 0.2375 0.015 40 11.5 2.46 2.259 0.201 3 -1 1 -1 -1 0.1125 0.035 40 11.5 1.92 1.808 0.112 4 1 1 -1 -1 0.2375 0.035 40 11.5 3.25 2.934 0.316 5 -1 -1 1 -1 0.1125 0.015 60 11.5 3.55 3.746 -0.196 6 1 -1 1 -1 0.2375 0.015 60 11.5 4.88 4.860 0.020 7 -1 1 1 -1 0.1125 0.035 60 11.5 4.33 4.373 -0.043 8 1 1 1 -1 0.2375 0.035 60 11.5 5.66 5.579 0.081 9 -1 -1 -1 1 0.1125 0.015 40 12.5 3.52 3.449 0.071 10 1 -1 -1 1 0.2375 0.015 40 12.5 4.84 4.883 -0.043 11 -1 1 -1 1 0.1125 0.035 40 12.5 4.3 4.287 0.013 12 1 1 -1 1 0.2375 0.035 40 12.5 5.62 5.814 -0.194 13 -1 -1 1 1 0.1125 0.015 60 12.5 5.93 5.636 0.294 14 1 -1 1 1 0.2375 0.015 60 12.5 7.25 7.150 0.100 15 -1 1 1 1 0.1125 0.035 60 12.5 6.71 6.519 0.191 16 1 1 1 1 0.2375 0.035 60 12.5 8.04 8.125 -0.085 17 -2 0 0 0 0.05 0.025 50 12 1.96 2.120 -0.160 18 2 0 0 0 0.3 0.025 50 12 4.62 4.760 -0.140 19 0 -2 0 0 0.175 0.005 50 12 2.87 3.003 -0.133 20 0 2 0 0 0.175 0.045 50 12 4.44 4.561 -0.121 21 0 0 -2 0 0.175 0.025 30 12 3.58 3.630 -0.050 22 0 0 2 0 0.175 0.025 70 12 8.41 8.462 -0.052 23 0 0 0 -2 0.175 0.025 50 11 3.03 2.509 0.521 24 0 0 0 2 0.175 0.025 50 13 7.78 7.279 0.501 25 0 0 0 0 0.175 0.025 50 12 4.52 4.796 -0.276 26 0 0 0 0 0.175 0.025 50 12 4.555 4.796 -0.241 27 0 0 0 0 0.175 0.025 50 12 4.735 4.796 -0.061 28 0 0 0 0 0.175 0.025 50 12 4.255 4.796 -0.541
    • International Journal of Advanced Research in Engineering and Technology (IJARET), ISSN 0976 – 6480(Print), ISSN 0976 – 6499(Online) Volume 5, Issue 4, April (2014), pp. 46-56 © IAEME 52 Table 5: Coefficients for the response function Coefficient. B0 B1 B2 B3 B4 B5 B6 B7 Value 4.51637 0.66333 0.39168 1.20663 1.18830 -0.30639 - 0.21515 0.36986 Coefficient. B8 B9 B10 B11 B12 B13 B14 Value 0.22235 0.00123 0.00123 -0.00127 -0.00002 -0.00002 - 0.00002 Correlation Coefficient R 0.99937 Variance explained % 99.87% Correlation the four variables with deposited copper layer thickness, the following response was obtained (7)00002.0 00002.000002.0001.0001.0001.0222.0 369.0215.0306.0188.1207.1392.0663.0516.4 43 423241321 2 4 2 3 2 2 2 14321 XX XXXXXXXXXX XXXXXXXy − −−−+++ +−−++++= For determination the significance of parameters in the above model, table (4) clearly shows Y (observed experimentally value) and y (predicated value by model) and its possible to compute the residual value as (8)Y-y iii =E 2 iE Value which are tabulated in the last column in table (4), this can be used to calculate 2 iE∑ . An estimate of the experimental error variance Sr2 which calculated as following: 009057.0 13 117735.0 S tscoeeficienmodelofnumberin15 experimatstheofnumberis28 131528 2 2 r == Σ = =−= γ γ iE The estimated variance of coefficients under nomenclature 2 bS was calculated by the following formula: (9)2 2 2 ∑ = X S S r b Where ∑X2 represents the sum of square of the corresponding elements of variable
    • International Journal of Advanced Research in Engineering and Technology (IJARET), ISSN 0976 – 6480(Print), ISSN 0976 – 6499(Online) Volume 5, Issue 4, April (2014), pp. 46-56 © IAEME 53 Table 6: F-test results for the mathematical model coefficients Coefficient. B B2 ∑ X2 Variance Sb2 =Sr2 /∑ X2 F value =B2 /Sb2 F0.95(1,13)=4,6 B1 0.663332 0.440009 24 0.000377 1165.974 S* B2 0.391681 0.153414 24 0.000377 406.5296 S B3 1.206632 1.455961 24 0.000377 3858.128 S B4 1.188301 1.41206 24 0.000377 3741.795 S B5 -0.30639 0.093875 48 0.000189 497.5161 S B6 -0.21515 0.046287 48 0.000189 245.3129 S B7 0.369859 0.136796 48 0.000189 724.9844 S B8 0.22235 0.049439 48 0.000189 262.0172 S B9 0.001227 1.51E-06 16 0.000566 0.00266 NS** B10 0.001227 1.51E-06 16 0.000566 0.002659 NS B11 -0.00127 1.62E-06 16 0.000566 0.002867 NS B12 -2.4E-05 5.52E-10 16 0.000566 9.76E-07 NS B13 -2.4E-05 5.52E-10 16 0.000566 9.76E-07 NS B14 -2.4E-05 5.52E-10 16 0.000566 9.76E-07 NS • *Significant • ** non-significant The F-test application lead to change the equation (3) to below equation (10) after we canceled the non-significant coefficients (10)222.0 369.0215.0306.0188.1207.1392.0663.0516.4 2 4 2 3 2 2 2 14321 X XXXXXXXy + +−−++++= According to equation (10) and by using Hook & Jeeves pattern [9], the optimum conditions were obtained .The optimum condition of studied variables in coded and real form are listed in table (7). Table 7: optimum conditions in coded and real values Variables Optimum coded Real X1 = Formalin concentration (M) -1.08 0.1125 M X2 = Copper sulfate concentration (M) -0.91 0.0159 M X3 = Temperature (° C) 1.63 66.3 C X4 = pH 2.67 13.33
    • International Journal of Advanced Research in Engineering and Technology (IJARET), ISSN 0976 – 6480(Print), ISSN 0976 – 6499(Online) Volume 5, Issue 4, April (2014), pp. 46-56 © IAEME 54 0.00 2.00 4.00 6.00 8.00 10.00 12.00 14.00 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 CopperlayerThikness(µm) Reduction ion Conc. (M) Figure (1): shows the effect of reduction ion concentration (formalin) on the deposited copper layer thickness 9.00 9.50 10.00 10.50 11.00 11.50 0 0.01 0.02 0.03 0.04 0.05 CopperlayerThicness(µm) Copper ion Conc. (M) Figure (2): shows the effect of CuSO4 concentration on the deposited copper layer thickness Dumesic et al. [10] using formaldehyde as a reducing agent he was reported that an increase in the formaldehyde concentration from 0.03 to leads to a linear increase in the initial deposition, and this is agree with figure (1). The overall reaction for electroless copper deposition, with formaldehyde (HCHO) as the reducing agent, is; Cu+2 + 2 HCHO + 4 OH - = Cu + 2HCOO - +2H2O+H2 (11) The effect of copper ions concentration on copper deposited layer thickness is shown in figure (2); there are high rate in increasing of copper deposited layer thickness through increasing in CuSO4 concentration, and this come from the fact that CuSO4 represent the copper ions source, which has ability to deposit under the experimental conditions.
    • International Journal of Advanced Research in Engineering and Technology (IJARET), ISSN 0976 – 6480(Print), ISSN 0976 – 6499(Online) Volume 5, Issue 4, April (2014), pp. 46-56 © IAEME 55 0.00 2.00 4.00 6.00 8.00 10.00 12.00 14.00 0 10 20 30 40 50 60 70 80 CopperLayerThicness(µm) Temperture (° C ) Figure (3): shows the effect of solution temperature on the deposited copper layer thickness 0.00 1.00 2.00 3.00 4.00 5.00 6.00 7.00 8.00 9.00 10.00 10.5 11 11.5 12 12.5 13 13.5 CopperLayerThicness(µm) pH solution Figure (4): shows the effect of solution pH on the deposited copper layer thickness Electroless copper deposition is affected by the pH in two distinct ways. First, OH- ions are reactants in the overall reaction (equation 11) and the below partial anodic reaction. Hydrolysis of Formalin: H2CO + H2O →H2C (OH)2 (12) H2C (OH) 2 + OH- → H2C(OH)O- +H2O (13) H2C(OH)O- →[HC(OH)O- ] ads +H ads (14) Where the subscript ads denote adsorption of species and [HC(OH) O- ] ads is electroactive species. Charge transfer, the electrochemical oxidation (desorption)of electroactive species, proceeds according to the reaction. [HC(OH)O- ] ads + OH- → HCOO- +H2O + e (15) Thus influence these reactions in a direct way (primary pH effects).Second, pH affects various phenomena associated with the structure and composition of the metal–solution interphase.
    • International Journal of Advanced Research in Engineering and Technology (IJARET), ISSN 0976 – 6480(Print), ISSN 0976 – 6499(Online) Volume 5, Issue 4, April (2014), pp. 46-56 © IAEME 56 All these phenomena modulate the rate of electroless copper deposition in an indirect way (secondarypH effects). CONCLUSIONS The Box-Wilson statistical experimental design procedure was seen to be applicable in modeling to evaluate the effect of important variables on copper electroless plating. The second order polynomial regression analysis of response y (deposited copper layer thickness) in term of four variables (i.e. concentration of reduction agent formalin (X1), copper ion concentration (X2), operating temperature (X3), and solution pH (X4) gives equation (10) which adequately describes the behavior of the electroless copper plating through studied range. The optimum conditions as predicated is concentration of reduction agent formalin (0.1125 M), copper ion concentration (0.0159 M), operating temperature (66.3 ӷ C), and solution pH (13.33). The deposited copper layer thickness increasing with increased in all four variables, these increasing continue until they reached to the optimum point and full down. ACKNOWLEDGMENTS The author would like to thank the Electrochemical Engineering Department at Babylon University for supporting and approving this research. REFERENCES [1] Klein et al., Electroless Plating Bath Composition and Method of Use, US patent 7686874 B2, Mar. 30, 2010. [2] Jun Li and Paul A. Kohl. The Acceleration of Nonformaldehyde Electroless Copper Plating, Journal of the Electrochemical Society, 149 (12) C631-C636 (2002). [3] Morishata et al. Electroless copper solution, US patent 40999741, Jul. 11, 1987. [4] T. Anik et al. Influence of pH Solution on Electroless Copper Plating Using Sodium Hypophosphite as Reducing Agent, Int. J. Electrochem. Sci., 7 (2012) 2009 – 2018. [5] MichinariSone et.al, Electroless copper plating using FeII as a reducing agent, ElectrochimicaActa 49 (2004) 233–238. [6] Zivorad R. Lazic, Design of Experiments in Chemical Engineering, Wiley-VCH VerlagGmbh& Co. KGaA, Germany, 2004. [7] Anderson, Chem. Eng. Prog., vol. 55, No. 4, (1959) P. 61, Statistics in the Strategy of Chemical Experiment. [8] William &Gertruds, Experimental Design, John Wiley & Sons, Inc., London, (1956). [9] Jeffwn and Hamada, Experiments; Planning, Analysis, John-Wiley and sons, New York, 2000. [10] J. Dumesic, The Rate of Electroless Copper Deposition by Formaldehyde Reduction, J. Electrochem. Soc., 121(1974) 1405. [11] Hameed Hussein Alwan, “Adsorption Mechanism for Corrosion Inhibition of Carbon Steel on HCl Solution by Ampicillin Sodium Salt”, International Journal of Advanced Research in Engineering & Technology (IJARET), Volume 4, Issue 7, 2013, pp. 236 - 246, ISSN Print: 0976-6480, ISSN Online: 0976-6499.